How Deep Research Started

Key Takeaways

You and your team have shipped deep research. Where did the idea come from? >> So around a year ago now, we were very excited about the progress internally on this new reinforcement learning algorithm. We were seeing a lot of progress on math problems and science problems and coding problems. And at the same time, we were very interested in agents generally and kind of wondered if we could apply the same algorithms to tasks that are maybe more in line with what the average user would do every day. And so the two first things we were thinking about were online browsing tasks and then we're also thinking about software engineering. I've been focusing on browsing to start with the math and coding problems that people were already training on. Those data sets already exist. You can have a math problem with a ground truth answer and you can train on those. But for browsing, it's kind of more open-ended. You don't really have data sets like that that exist. [music] So we really started by grounding the research and what product use cases we actually wanted the final model to be good at. So, we literally would write out just a list of things like I hope the model that could find this list of products for me and rank them by like these reviews from Reddit or something like